Analytics Engineer

Leeds
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Manager (Analytics)

Data Engineer (Analytics)

Data Engineer (Analytics)

Hybrid Data Engineer for Analytics & ML Platforms

Data Analyst & Cloud Analytics Engineer

Data Scientist & Analytics Engineer

Are you passionate about building scalable, analytics-ready data models that power business intelligence and AI? I'm looking for an Analytics Engineer to join a global organisation that's investing heavily in a modern, AI-ready data platform - and this is your chance to help shape it from the ground up.

You'll be part of a newly formed, high-impact Data Team working in a fast-paced, collaborative, and entrepreneurial environment. Based in their modern Leeds office, you'll spend 4 days a week on-site, working closely with engineers, analysts, and business stakeholders.

🚀 About the Platform:

This greenfield initiative is focused on building a next-gen data ecosystem with a tech stack including:

Snowflake for cloud data warehousing
dbt for transformation and modelling
Azure for cloud infrastructure and orchestration
Fivetran for automated data ingestion
Power BI and other modern BI tools for reporting and visualisation🧠 What You'll Do:

Design and implement scalable, well-documented data models in Snowflake using dbt
Build curated, reusable data layers that support consistent KPIs and enable self-service analytics
Collaborate with Power BI developers to deliver insightful, high-performance dashboards
Work with Data Engineers to optimise data ingestion and orchestration pipelines using Azure Data Factory and Fivetran
Apply best practices in dimensional modelling, layered architecture, and data quality✅ What We're Looking For:

Strong experience in data modelling and SQL
Hands-on experience with dbt and cloud data platforms like Snowflake or Azure Synapse Analytics
Solid understanding of modern data stack principles, including layered modelling and data warehouse design
Excellent communication skills and the ability to work with stakeholders across technical and non-technical teamsNice to have:

Experience with Power BI or similar BI tools
Familiarity with CI/CD practices in data environments
Exposure to data governance and metadata management🎁 What's in It for You:

Salary from £50,000 to £65,000depending on experience
Discretionary bonus
4% employer pension contribution
25 days holiday(plus bank holidays), increasing with service
Holiday purchase scheme
Electric/hybrid car scheme

Please Note: This is a permanent role for UK residents only. This role does not offer Sponsorship. You must have the right to work in the UK with no restrictions. Some of our roles may be subject to successful background checks including a DBS and Credit Check.

Tenth Revolution Group / Nigel Frank is the UK's leading recruiter for Data and AI roles. We proudly sponsor SQLBits and the London Power BI User Group. For a confidential discussion about this role or your job search, contact (url removed)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.